Imaging systems are increasingly used in a number of applications. These include remote sensing, medicine and manufacturing, including semiconductor fabrication, yield management and process diagnostics. One manner in which imaging systems are used is in comparing corresponding images. For example, a semiconductor wafer may include a number of substantially identical dies. An imaging system may capture corresponding images of two or more dies and compare the images to identify defects, differences, or irregularities. Imaging systems typically capture two dimensional attributes of selected attributes of three dimensional objects.
In order to compare the spatial location of objects represented in images, an imaging system first registers or correlates the corresponding images. This registration process may be described as an identification and alignment of a first image and a second, corresponding image, to account for any shift between the respective images. The registration step is important for making a meaningful comparison of the corresponding images. If the corresponding images are misaligned, the comparison of the images will be effected negatively. One method for performing this alignment is known as feature-based registration. As its name suggests, feature-based registration includes identifying geometric features on each image, establishing correspondence, and using the coordinates of these features to identify corresponding points on a corresponding image.
However, feature-based registration has significant disadvantages. Primarily, feature-based registration techniques are time consuming and require significant computational resources. In application, common features may become difficult to extract in the presence of noise, often leading to reliability issues. Further, in some applications it is desirable to rapidly register a plurality of corresponding pairs of complex images. Accordingly, a lengthy registration process, such as that associated with feature-based registration, limits the overall operational speed and throughput of the imaging system. Additionally, as the size of devices formed on semiconductor dies decreases, imaging system will be required to inspect increasingly small structures. As such, errors made in the registration of corresponding images will be amplified.